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Practical lessons learned from real-world implementation of the molecular classification for endometrial carcinoma
Inês Moreira1, Marta Ferreira1, Sofia Garcia2
1Medical Oncology Department, Portuguese Institute of Oncology of Porto, Rua Dr. António Bernardino de Almeida 865, 4200-072 Porto, Portugal.
Objectives:
This study aimed to explore the practical organisational aspects and difficulties in the implementation of the molecular classification of endometrial carcinoma (EC), and to demonstrate its potential impact in prognostic risk group classification.
Methods:
We conducted a multicentre, retrospective cohort study of 230 patients with EC diagnosed between 2019 and 2022. Sample processing, clinicopathological, treatment and follow-up data were collected. Molecular classification was obtained by p53 and mismatch repair proteins immunohistochemistry, and POLE next-generation sequencing.
Results:
Implementation was achieved through centralization of molecular analysis. In practice, it was possible to optimise turnaround times of complete integrative reports for hysterectomy specimens to a median time of 18 workdays. If genetic study was started in endometrial biopsies before surgery, 82.0% were available at the time of multidisciplinary tumour board, compared to 8.4% if performed in hysterectomy. ECs were classified as follows: 37.8% no specific molecular profile, 31.7% p53 abnormal, 24.3% mismatch repair deficient, and 6.1% POLE mutant. Integration of these results with traditional clinicopathologic factors led to a change in prognostic risk group in 15 (6.5%) patients, most being initially allocated to high-intermediate (n = 8) and low (n = 5) risk groups. Eight patients changed to a higher risk, and 7 to a lower risk group, whereas 2 remained in the same group.
Conclusions:
Centralization of EC molecular classification is a feasible option for countries with limited resources. Optimization of workflows may be achieved by earlier analysis in biopsies and prioritisation of patients whose results imply changes in risk group classification.
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